Drug-Induced Immune Hemolytic Anemia: Detection of New Signals and Risk Assessment in a Nationwide Cohort Study.
Julien MaquetMargaux LafaurieMarc MichelMaryse Lapeyre MestreGuillaume MoulisPublished in: Blood advances (2023)
More than 130 drugs have been suspected to induce immune hemolytic anemia. Comparative studies measuring the risk of drug-induced immune hemolytic anemia (DIIHA) are lacking. We aimed 1) to detect new signals of DIIHA, excluding vaccines 2) to assess the association between all suspected drugs and the occurrence of immune hemolytic anemia in a nationwide comparative study. The new signals were identified using a disproportionality study (case/non-case design) in the World Pharmacovigilance Database, Vigibase®, among the cases of adverse drug reactions reported up to February 2020 (>20 million). We then conducted a comparative study in the French National health database that links sociodemographic, out-of-hospital and hospital data for the entire population (67 million individuals). The associations between the exposure to drugs (those already reported as DIIHA, plus new signals identified in Vigibase®) and incident cases of immune hemolytic anemia (D59.0 and D59.1 diagnosis codes of the International Classification of Diseases, version 10) between 2012 and 2018 were assessed with case-control and case-crossover designs. In Vigibase®, 3,371 cases of DIIHA were recorded. Fifty-nine new signals were identified resulting in a final list of 112 drugs marketed in France and measurable in the nationwide cohort (n=4,746 patients with incident immune hemolytic anemia included in the case-control analysis matched with 22,447 controls from the general population). We identified an association between immune hemolytic anemia occurrence and some antibiotics, antifungal drugs, ibuprofen, acetaminophen, furosemide, azathoprine and iomeprol.
Keyphrases
- drug induced
- adverse drug
- liver injury
- chronic kidney disease
- iron deficiency
- case control
- risk assessment
- electronic health record
- healthcare
- cardiovascular disease
- machine learning
- emergency department
- randomized controlled trial
- clinical trial
- pulmonary embolism
- big data
- candida albicans
- open label
- human health
- cross sectional
- heavy metals
- data analysis
- label free